Summary: Developing detailed a priori 3D models of large environments to aid in
robotic navigation tasks
Brad Grinstead*
, Andreas Koschan, Mongi A. Abidi
Imaging, Robotics, and Intelligent Systems Laboratory
334 Ferris Hall
Department of Electrical & Computer Engineering
The University of Tennessee
Knoxville, TN 37996
ABSTRACT
In order to effectively navigate any environment, a robotic vehicle needs to understand the terrain and obstacles native to
that environment. Knowledge of its own location and orientation, and knowledge of the region of operation, can greatly
improve the robot's performance. To this end, we have developed a mobile system for the fast digitization of large-scale
environments to develop the a priori information needed for prediction and optimization of the robot's performance. The
system collects ground-level video and laser range information, fusing them together to develop accurate 3D models of
the target environment. In addition, the system carries a differential Global Positioning System (GPS) as well as an
Inertial Navigation System (INS) for determining the position and orientation of the various scanners as they acquire
data. Issues involved in the fusion of these various data modalities include: Integration of the position and orientation
(pose) sensors' data at varying sampling rates and availability; Selection of "best" geometry in overlapping data cases;
Efficient representation of large 3D datasets for real-time processing techniques. Once the models have been created, this